When people sneeze, they can shoot out respiratory system-related pathogens at a high speed. These can infect humans in many ways – most often through contacting mouth, nose, and eyes.

To avoid infections, you should avoid outdoor activities – especially in crowded areas. It's also important to sanitize your hands often and not to rub your eyes with your hands.

I'm in China, and my plans for Lunar New Year are now ruined. So I decided to stay home and create this tutorial on how to obtain genetic sequence data of 2019-nCoV and perform a Sequence Alignment on it with MAFFT.

I hope this article raises your interest in bioinformatics research, so you can help scientists fight these viral outbreaks.

What is Sequence Alignment? And what is MAFFT?

Sequence Alignment is a way of arranging DNA, RNA, or protein to identify regions of similarity that may reveal functional, structural or evolutionary relationships between the sequences. A recent publication suggested cross-species transmission from snake to human with the help of sequence alignment through MAFFT.

MAFFT (Multiple Alignment using Fast Fourier Transform) is a multiple sequence alignment program published in 2002. You can use it to perform sequence alignment for RNA sequences. Coronaviruses are, for example, viruses with a single-stranded RNA enveloped in a shell derived from the cell membranes of the host.

Where Can You Obtain RNA Sequence Data?

The latest update of 2019-nCoV can be found on NGDC (National Genomics Data Center of China). In this tutorial, we will analyze the 2019-nCoV virus and the SARS-CoV virus found inside the NCBI (National Center for Biotechnology Information) data bank.

I have copy and pasted the data into a file with the name of the virus. It should look something like the data in the screenshot above, with an index number followed by codes in a batch size of 10, for a total of 60 codes per line, separated by spaces.

How to Perform Sequence Alignment on 2019-nCoV with MAFFT

First, you need to install MAFFT. You can install it via Anaconda with the following commands.

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